Course timing synchronization

ABSTRACT

A system for determining the burst start timing of a signal includes logic configured to receive the signal, generate correlation moduli and generate a first timing output based on the correlation moduli. The logic may also be configured to receive operating mode information and timing information and generate search controls. The logic may further be configured to identify a maximum of the correlation moduli using the search controls and determine a second timing output associated with the maximum correlation modulus. The second timing output represents a more accurate approximation of a burst start time than the first timing output.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.11/560,528 filed Nov. 16, 2006, which is a continuation of U.S. patentapplication Ser. No. 09/974,093 filed Oct. 10, 2001 (now U.S. Pat. No.7,154,967), the disclosures of which are incorporated herein byreference. This application also claims priority to the followinginternational patent application: European Application No. 01400494.9,entitled “METHODS AND APPARATUS FOR EFFICIENT AND ACCURATE COARSE TIMINGSYNCHRONIZATION IN BURST DEMODULATORS,” Joseph Boutros et al., filedFeb. 26, 2001.

BACKGROUND

FIGS. 1A and 1B illustrate a prior-art Hybrid Fiber-Coax (HFC) cablesystem 100 that is compatible with the cable industry standard Data overCable System Interface Specification (DOCSIS) for providing Internetaccess to selected cable customers via so called Cable Modems (CMs).FIG. 1A is a top-level view of the cable system. FIG. 1B providesadditional detail of the Customer Premises Equipment (CPE) of FIG. 1A.In FIG. 1B, CM 4000 provides a computer industry standard Ethernetinterface to PC 5000 and bridges the Ethernet interface with the coaxdistribution of the cable system. CM 4000 implements both an RFModulator and an RF Demodulator. These circuits enable digital TDMAburst-modulated communications over dynamically manager upstream anddownstream RF channels and in accordance with the DOCIS standard.

An RF Modulator 3000 and RF Demodulator 1000, complementary to those ofthe cable modem, are implemented in a DOCSIS compatible Cable ModemTermination System (CMTS) 500, which as the name implies, providestermination for the Cable Modem of the CPE. Multiple instances ofModulator 3000 and Demodulator 1000 are provisioned to support thosecustomers having CM service. Control, MAC, Framing 2000 bridges all ofthe provisioned DOCSIS RF interfaces with one or more packet-basednetworks. These packet networks may include local area networks,intranets, and the Internet. While FIG. 1A shows the CMTS 500implemented in a Head End or Primary Hub, theoretically it is possibleto implement the CMTS anywhere upstream from the CM. Each demodulator1000 provides outputs to the Control, MAC, Framing 2000 that includeDetected Symbols 1200, and more generally, other status and controlsignals.

FIG. 2A provides a general conceptual block diagram of the digital burstDemodulator 1000 in the CMTS 500. Front-End 600 isolates one modulatedcarrier from the carrier multiplex in the Received Spectrum 1100,baseband converts the signal, and passes the resulting signal 1105 tothe Burst and Timing Synchronization circuit 1500. (In other contextsthe Front-End 600 might be considered as a function prior to, and notpart of, the demodulator.) The Recovered Signal Samples 1106, at theoutput of circuit 1500, are discrete signal samples at the symbol rate(or a multiple thereof). Equalizer 1600 compensates for signaldistortion not compensated by the pre-equalizer in the cable modem (CM)and also suppresses ingress noise. At the output of this stage, theEqualized Signal Samples 1107 are not synchronized in terms of carrierphase. This is the task of the Rotator 1700 and Phase Estimator 1900that follow the Equalizer 1600. Detector 1800 subsequently outputsDetected Symbols 1200.

In burst demodulator applications, such as for the CMTS, the informationis conveyed via bursts of symbols. The demodulator must first detect andthen decode the bursts. In contrast to analog demodulators, the decodefunctions are not linear analog circuits that operate continuously, butrather are digital clocked circuits that must be synchronized with theincoming symbols in order to operate. Yet, the symbols are sentasynchronously, in the sense that there is no common clock reference forboth the CM and the CMTS. The Burst and Timing Synchronization 1500 ofFIG. 2A provides the required burst detection and synchronization and isthus critical to the operation of the demodulator.

The synchronization circuitry 1500 may be further partitioned intocoarse timing synchronization and fine timing synchronization. This nextlevel of detail is conceptually illustrated in FIG. 2B. Coarse timingsynchronization is also referred to as burst synchronization. Finetiming synchronization is also referred to as symbol timingsynchronization or symbol timing recovery.

The role of the coarse timing circuitry is to establish the burst timingto an uncertainty of less than T/2 (0.5 symbol period). The coarsetiming circuitry provides the burst timing to the fine timing circuitryand generally to other circuits in the demodulator. Neither the finetiming synchronization, nor the subsequent phase and frequency recoveryprocesses, can be utilized prior to a burst start being detected, asthese processes need to be coarse-synchronized with the corresponding CM(for which the demodulator has been provisioned). The role of the finetiming synchronization circuitry is to provide the exact sampling phasenecessary for low error rate symbol detection.

In CMTS applications, the coarse timing circuitry must contend withsystem operation under normal data traffic conditions (traffic mode) andduring so-called ranging periods (ranging mode). Ranging is a process bywhich the CMTS manages the allocation and usage density of time-slotsfor each of multiple CMs generally assigned to each upstream channel.More specifically, the CMTS uses ranging periods to ascertain theround-trip delay for a specific CM and to subsequently command that CMto operate with a corresponding transmit time-offset. Ranging isperformed whenever a CM is initialized and registered by the network andwhenever the CMTS suspects that time-slot integrity may have been lost.The ranging calibration process is performed for every CM on the channeland enables the system to smoothly operate at high effective throughputduring traffic mode. During subsequent traffic mode operation, from theperspective of the CMTS, the CMs transmit upstream data bursts withintheir assigned time-slots as though they were all located at a uniformand zero distance from the CMTS.

Ranging periods represent the most problematic operating condition forthe CMTS, as the coarse timing circuitry has to reliably (but notfalsely) detect bursts that may (or may not) arrive with a huge timinguncertainty (typically up to 3 ms). During traffic mode, the CM isoperating with a time slot and delay compensating transmit time-offset,both assigned (and known) by the CMTS as discussed above. Accordingly,the burst timing uncertainty in traffic mode is reduced to time-offsetcorrection errors (typically no greater than 1.1 symbol periods).

As indicated by the switch in FIG. 2B, the coarse timing synchronizationcircuitry is operated differently in the two operating modes. Duringranging, the burst timing is effectively unknown and burst detection isrequired to initiate frame synchronization. During traffic mode, burstdetection is not utilized, and the frame synchronization is initiatedusing the CMTS's knowledge of the burst timing, gained during the priorranging period.

Burst detection must be as sensitive as possible, so that demodulationof valid bursts is able to start with the shortest possible delay. Delayin signaling the detection of a valid burst may result in the loss ofinitial symbols of the burst and more generally requires increaseddemodulator complexity to prevent or minimize such losses. Moreover, thecoarse timing circuitry must have the ability of to reliably distinguishbetween received noise and received symbol bursts. Two separate errorprobability indicators characterize this ability. The NondetectionProbability, or Pnd, is the probability that an actually transmittedburst will not be detected. The False Alarm Probability, or Pfa, is theprobability of declaring that there is a burst when no burst is actuallytransmitted. Clearly, smaller error probabilities are better. Pnd mustbe low and Pfa must be very small.

The time necessary for a CM to become registered by the network during aranging opportunity is a key concern, as the system must systematicallyensure that the CM is detected and demodulated. The mean registrationtime depends of the probability Pnd, which depends on both the modemperformance and the collision probability.

A common method of determining the coarse timing of the start of aranging burst is the use of power estimation. This is the method shownin FIG. 2B. Generally, this approach performs a long signal integrationto estimate the received signal power and compares this estimated powerto a predetermined threshold to ascertain if more than thermal noise ispresent on the channel's carrier frequency. Unfortunately, this methodhas a number of problems.

Because power estimation bases burst detection on comparing theestimated power with a predetermined threshold, it is undesirablysensitive to power level (i.e., signal-strength) variations associatedwith different operating conditions (such as variations in attenuationattributable to variations in path lengths). Furthermore, its operationmay be compromised by power variations local to the receiver, such asthose attributable to the automatic gain control (AGC) of the precedingstages.

Estimation of the received signal power is performed by integrating theinstantaneous signal power over a given time window. The integrationtime (i.e., the duration of the integration window) is a carefullychosen compromise that impacts several key aspects of demodulatorperformance. Increasing the integration time beneficially reduces thecontribution of noise-induced errors in the final power estimate.Unfortunately, increasing the integration time detrimentally increasesburst detection latency and reduces the slope of the estimated powerfunction. Increasing burst detection latency requires devoting a largerportion of each burst transmission to the overhead associated withdetecting the start of the burst. This increased overhead decreases theeffective transmission rate on the upstream channel.

Reducing the slope of the estimated power function reduces the accuracywith which the burst start may be detected. As a consequence, powerestimation alone does not deliver a sufficiently accurate indication ofburst timing for use in direct synchronization of other demodulatorsynchronization processes. Some manner of complementary (additional)timing estimation (such as frame synchronization, discussed next) mustbe relied upon to establish the burst timing with sufficient accuracy tobe used as the basis for beginning the other synchronizations.

The frame synchronization circuitry handles smaller timing uncertaintiesthan are required of burst detection. Frame synchronization is alwaysused in traffic mode, and as illustrated, it also may be used in rangingmode to complement (assist) burst detection. The frame synchronizationis often implemented by correlation of the received signal with a knownpreamble. The preamble is specifically chosen such that the position ofthe first symbol of the burst corresponds to a maximum of thecorrelation modulus. Typically, some form of time-indexed history bufferretains the most recent correlation moduli. Searching the history bufferwithin a time window delimited by the power estimation circuitryidentifies the correlation maximum.

An approach is needed to burst detection that is superior to powerestimation. A burst detection approach is needed that can reliablydistinguish between received noise and symbol bursts, with low Pnd andvery small Pfa. A burst detection approach is needed that has minimallatency and high accuracy, preferably within T/2, where T denotes thesymbol period. (I.e., the reported location of the start of the burst isaccurate within one-half symbol period of the actual start of theburst). A burst detection approach is needed that is sensitive to smallpower transitions, but has reduced dependence on variations in signallevel associated with different operating conditions, and is notcompromised by local AGC operation. A burst detection approach is neededthat minimizes hardware and overall implementation complexity.

BRIEF DESCRIPTION OF DRAWINGS

FIGS. 1A and 1B illustrate a prior-art HFC cable system. FIG. 1A is atop-level view of the cable system. FIG. 1B provides additional detailof the CPE of FIG. 1A.

FIG. 2A provides internal architectural detail of Demodulator 1000 ofFIG. 1A.

FIG. 2B provides detail of a prior art implementation of the Burst andTiming Synchronization 1500 of FIG. 2A.

FIG. 3 provides detail of an illustrative implementation of the Burstand Timing Synchronization 1500 of FIG. 2A, providing additional systemcontext for the present invention.

FIG. 4 is a conceptual block diagram of the Coarse TimingSynchronization block 1550 of FIG. 3, at a first level of detail.

FIG. 5 provides detail of an illustrative implementation of the CoarseTiming Synchronization 1550 of FIG. 4.

SUMMARY

Aspects described herein provide improved accuracy for determining thecoarse timing of the start of data bursts (e.g., as received byburst-demodulators). Burst detection with high accuracy (withinone-quarter of a symbol period, T/4, in an illustrative embodiment) maybe achieved together with good sensitivity, reduced dependence on signalstrength, reduced susceptibility to local AGC operation, low errorprobabilities, very low latency, and a highly efficient use of hardware.Aspects described herein may use a combination of selectively chosenautocorrelation sequences, rejection of signal level inducedautocorrelation variations, and parabolic interpolation.

In accordance with an exemplary implementation, the burst detectionprocess is based on an evaluation of correlation moduli. Morespecifically, autocorrelation may be performed on the isolated andbaseband converted received signal using a preamble-embedded correlationsequence selected to provide desired autocorrelation properties. Inparticular, the correlation sequence may be chosen such that a steeplysloped peak characterizes the autocorrelation time-domain response tothe passing of a received preamble with the embedded sequence. In anillustrative but not limiting embodiment, a sequence from the ConstantAmplitude Zero Auto-Correlation (CAZAC) family of sequences is used.

A number of hardware efficiencies may be realized in the correlationstage associated with a first exemplary implementation. First, it doesnot require a prior burst detection stage (in contrast to prior artcorrelation stages used for frame synchronization). Second, the samecorrelations that are used to detect the burst start in ranging mode arepreferably also used for the frame synchronization in the traffic mode.Furthermore, the autocorrelation circuit is preferably used multipletimes per clock period (by sequential operation in separate sub-multiplephases of the clock) to provide a level of accuracy that would otherwiserequire a corresponding multiple of autocorrelation circuits.

In an exemplary implementation, the autocorrelation output may be fed toboth a contrast detection function and a correlation maximizationfunction. For use in ranging mode, the contrast detection generates ametric (referred to as the contrast ratio) by evaluating the currentcorrelation modulus relative to adjacent correlation moduli in a manner(defined by a specific contrast function, C(t)) that is sensitive toburst-start signal level transitions, but is insensitive to power level(i.e., signal-strength) variability associated with different operatingconditions. When the contrast ratio exceeds a chosen threshold, thecontrast detection signals an intermediate burst indication to thecorrelation maximization function.

In an exemplary implementation, the correlation maximization functionincludes a time-indexed history buffer that includes the most recentsamples of the autocorrelation output. Either the burst indication fromthe contrast detection function (when in ranging mode), or a prioriburst timing knowledge from the CMTS (when in traffic mode) may be usedto define a time window within the history buffer and to initiate thesearch for the autocorrelation maximum within the window. For example, asearch, bounded by the time window, may be made for the maximumautocorrelation modulus. The time associated with the correlationmaximum is the approximate time of the start of the burst. Burst-startindications so identified by the search are accurate within thesub-clock multiple associated with the autocorrelation results (one-halfof a symbol period, T/2, in the illustrative embodiment). Parabolicinterpolation may also be subsequently applied to deliver an overallburst-start indication with additional accuracy (within one-quarter of asymbol period, T/4, in the illustrative embodiment).

DETAILED DESCRIPTION

The present invention is applicable to a variety of burst detectionapplications. In an illustrative but not limiting embodiment, the CoarseTiming Synchronization block 1550 of the present invention findsparticular application in the system environment previously defined bythe high level functionality of the Burst Timing and Synchronizationblock 1500 of FIG. 2A, but as further detailed by FIG. 3, instead ofFIG. 2B. In the Burst Timing and Synchronization block 1500 of FIG. 3,Fine Timing Synchronization 1580 is preferably implemented using thewell-known Meyr Algorithm 1570. It is also preferable to include in theimplementation the Optional Channel Estimation 1585 and Optional PowerEstimation and Scaling 1590.

FIG. 4 is a conceptual block diagram of the Coarse TimingSynchronization block 1550 of FIG. 3, at a first level of detail, inaccordance with the present invention. As introduced previously anddiscussed in detail later below, an autocorrelation circuit 4100 is usedin conjunction with a selected sequence embedded in the preamble, suchthat the time domain response of the autocorrelation output 4110 has asteeply sloped peak (i.e., steeply sloped level transitions) in responseto the reception of the selected sequence. The autocorrelation moduli(the samples on 4110) are passed both to Contrast Detection 4200 andCorrelation Maximum Search 4300.

The Contrast Detection 4200 uses a contrast function (detailed laterbelow) to evaluate whether a burst has been observed. The contrastfunction is sensitive to received signal transitions attributable to theonset of a burst while insensitive to variations in the level of thereceived signal attributable to different operating conditions, Upondeciding that a burst has been detected, Contrast Detection 4200activates the BURST_DETECT 4210.

The Correlation Maximum Search 4300 retains a running (constantlyupdated) collection of recent correlation moduli. Based on the a prioriknowledge by the CMTS (4220) of the burst timing, or upon receipt of theBURST_DETECT signal 4210, the Correlation Maximum Search 4300 starts asearch to identify the correlation maximum, which is output at 4310.Whether the a priori knowledge or the BURST_DETECT is used, isdetermined as illustrated, in accordance with MODE 4270. The searchwindow size should correspond to the extent of time uncertainty for thesearch and is selected also based on the system mode (i.e., ranging vs.traffic; as indicated by MODE 4270), and more generally on functionalconfiguration (e.g., baud rate), and other system constraints. The timeassociated with the correlation maximum is the approximate time of thestart of the burst. Parabolic Interpolation 4400 is further used toincrease the accuracy of the final burst detection output,COARSE_BURST_START 1555.

FIG. 5 is an illustrative implementation of the Coarse TimingSynchronization block 1550 of FIG. 3, providing additional detail of theinvention. The Steeply Sloped Autocorrelation function of FIG. 4 isreferred to here as CAZAC Correlation Engine (5100). It computes theautocorrelation of the quadrature signal pair 1105 (output from thereceiver front-end) and provides samples on CORR_MOD 4120 to FIFO 4150.As discussed in the background, operation switches repeatedly betweenthe Ranging mode and the Traffic mode under control of the CMTS via theMODE 4270 signal. In the Traffic mode, the burst start position is knownwith an uncertainty of +1.1 symbol periods for the highest baud rate. Inthe Ranging mode, the burst start position is known with a largeuncertainty (typically 3 ms).

In the present invention, Window Start & Size Logic 4250 sets theposition of the burst start-time uncertainty-window in accordance withthe different conditions encountered in these two modes. In the Rangingmode, the window start is controlled by the BURST_DETECT (4210)delivered by the Contrast Detection circuit (4200). The window size mustbe sufficiently large to compensate for the uncertainty due tolimitations in the contrast detection function. In the Traffic mode, thewindow start is controlled by the a priori knowledge of the CM timingoffset. This knowledge was obtained by the CMTS during a previousranging operation. The window size in this mode must be sufficientlylarge to compensate for the uncertainty of the timing offset, due tolimitations in the ranging process.

CAZAC Correlation Algorithm

In the illustrative embodiment it is assumed that the preamble of thereceived bursts contains a 26-symbol sequence in accordance with theConstant Amplitude Zero Auto-Correlation (CAZAC) family of sequences.(The invention is not restricted to sequences from the CAZAC family.Other sequence families that provide similar steeply slopedautocorrelation responses will also suffice.) The symbols preferablytake two opposite values (antipodal signals) chosen in the QPSK or the16-QAM constellations, but other choices are also possible. The26-symbol CAZAC sequence is derived from an original 16-symbol sequenceby appending the first 5 symbols at its end and copying the last 5symbols at the beginning.

${{Let}\mspace{14mu} {R_{xx}^{Periodic}(\tau)}} = {\sum\limits_{i = 0}^{{L\; \_ \; {CORR}} - 1}{x_{i}^{*}{x\left( {i - \tau} \right)}{{mod}{L\_ CORR}}}}$

denote the periodic autocorrelation function of the 16-symbol CAZACsequence, where the variable (tau) is an integer. L_CORR stands for theCorrelation length, which is equal to 16. The symbols x, of thesequence, i=16 . . . 16, are chosen such that:

R_(xx)^(Periodic)(0) = 32, and R_(xx)^(Periodic)(τ) = 0.0for  τ = −5  … + 5  and  τ ≠ 0

The CAZAC Correlation Engine 5100 computes a scalar product (also calledcorrelation) between the 16 symbols x_(i) of the CAZAC sequence andsamples r(t+i×T_(s)) extracted from the received signal. Notice that thesamples r(t+i×T₅) are separated by a symbol period T_(s). The evaluatedscalar product is:

${R_{rx}\left( {t,\tau} \right)} = {\sum\limits_{i = 1}^{16}{{r\left( {t + {\left( {i - \tau} \right)T_{s}}} \right)}x_{i}^{*}}}$

Note that R_(rx)(t,τ)=R_(rx)(t−τ×T_(s),0), it shall be derived fromR_(rx)(t,0).

As a preferred approach in the illustrative embodiment, to guarantee anuncertainty interval less than T_(s)/2, the correlation is computedtwice per symbol period, i.e. the scalar product R_(rx)(t,0) isevaluated for t=k×T_(s) and t=(k+½)×T_(s), where k is an integer. Thusthe CAZAC Correlation Engine 5100 is operated twice per clock period.

Contrast Algorithm

The function of the contrast algorithm is to decide whether or not aburst is present in the received signal. The decision is taken aftersome signal processing based on the preamble content. To enable thisprocessing, FIFO 4150 holds a moving sequence of 11 correlation moduli,including the “center” modulus 4160, 5 “previous” moduli 4170, and 5“next” moduli 4180. These moduli are provided to the Contrast Detection5100 to enable evaluation of the contrast algorithm, described below. Aninternal flag called BurstFound is set to 1 when the contrast algorithmdecides that a burst is present, otherwise this flag is always set to 0.

For a given value of time t, we assume that 2×W+1 (11 in theillustrative embodiment) scalar product values R_(rx)(t,τ) are available(e.g., from the FIFO), for τ=−W . . . +W. These 2×W+1 correlations areused to get a contrast defined by:

${C(t)} = \frac{{{R_{rx}\left( {t,0} \right)}}^{2}}{\sum\limits_{{\tau = {- W}},{\tau \neq 0}}^{+ W}{{R_{rx}\left( {t,\tau} \right)}}^{2}}$

In a preferred implementation, W is set to 5. Now, fix a given thresholdS. The following rule is applied to make a decision:

If C>S then BurstFound=1, otherwise BurstFound=0.

The threshold S is appropriately selected when Pnd and Pfa are low andlead to a low probability of missing a burst.

Correlation Maximization

The Correlation Maximum Search 5300 finds the maximum of the correlationmodulus |R_(rx)(t,τ)|², within a dynamically determined range around theexpected time t. This range is associated with a burst-starttime-uncertainty window that is defined in the illustrative embodimentby the Window Start & Size Logic 4250 via Window Start 4260 and WindowSize 4270. Delayed correlation moduli 4190 are received from the outputfrom FIFO 4150 and a running (constantly updated) history buffer ofthese moduli is maintained as required to support the search. In apreferred embodiment, the history buffer is offset counter-indexed, andthereby effectively time-indexed. In the Ranging mode, the search isinitiated by an appropriately delayed version of BURST_DETECT 4210, fromthe Contrast Detection 5200. In the Traffic mode, the search isinitiated by an a priori knowledge of the CM timing by the CMTS 4220.Once the correlation maximum is found, the time associated with it istaken to be the approximate time of the start of the burst. The timeassociated with the correlation maximum is provided (in the form of anoffset pointer with resolution to T/2) as MAX_POSITION 4310 to theSynchroburst Generation 4500.

Parabolic Interpolation

The Correlation Maximum Search 5300 provides the Parabolic Interpolation5400 with the amplitude values of three sequential correlation moduliread from the history buffer: the maximum correlation modulus, theimmediately adjacent previous (T/2 earlier in time) correlation modulus,and the immediately adjacent next (T/2 later in time) correlationmodulus. In the equation below, CorrModMax, CorrModPrev, and CorrModNextrespectively represent these moduli. In FIG. 5, CORR_MOD_TRIO 4306collectively represents the three moduli.

The Parabolic Interpolation 5400 uses these three moduli to generate atiming offset to further refine the accuracy of the burst start time.The parabolic interpolation timing offset, Δt_(Parinter), expressed insymbol periods, is defined by:

${\Delta \; t_{Parinter}} = {\frac{1}{4} \times \frac{{CorrMod}_{Prev} - {CorrMod}_{Next}}{{CorrMod}_{Prev} - {2 \times {CorrMod}_{Max}} + {CorrMod}_{Next}}}$

This timing offset is appropriately quantified to a predetermined set ofallowed time values, which in the illustrative embodiment consist of−(¼×T_(s)), 0, and +(¼×T_(s)), collectively represented by quantifiedoffset 4410.

Synchroburst Generation

Synchroburst Generation 4500 adds the quantified offset 4410 from theParabolic Interpolation 5400 to the MAX_POSITION 4310 time value andgenerates COARSE_BURST_START 1555 in a manner that indicates the startof the detected burst with accuracy within T/4.

Conclusion

Although the present invention has been described using particularillustrative embodiments, it will be understood that many variations inconstruction, arrangement and use are possible consistent with theteachings and within the scope of the invention. For example,bit-widths, clock speeds, and the type of technology used may generallybe varied in each component block of the invention. Also, unlessspecifically stated to the contrary, the value ranges specified, themaximum and minimum values used, are merely those of the illustrative orpreferred embodiments and should not be construed as limitations of theinvention. Certain preferred options used in the illustrativeembodiments are not limitations of the invention. Specifically, otherembodiments may use different correlations in the ranging and trafficmodes. Functionally equivalent techniques known to those skilled in theart may be employed instead of those illustrated to implement variouscomponents or sub-systems. For example, the autocorrelation sequence maybe chosen from other than the CAZAC family of sequences. The contrastfunction is not limited to the specific contrast function of theillustrative embodiment. Different approaches may be equivalently usedto implement the FIFO functionality for the contrast detection, or thehistory buffer for the Correlation Maximum Search. All such variationsin design comprise insubstantial changes over the teachings conveyed bythe illustrative embodiments. The names given to interconnect and logicare illustrative, and should not be construed as limiting the invention.It is also understood that the invention has broad applicability toother communications and network applications, and is not limited to theparticular application or industry of the illustrated embodiments. Thepresent invention is thus to be construed as including all possiblemodifications and variations encompassed within the scope of theappended claims.

1. (canceled) 2-29. (canceled)
 30. A method comprising: receiving, at anetwork device, a signal; generating, at the network device, correlationmoduli based on the received signal; generating, at the network device,a first timing output based on the generated correlation moduli;generating, at the network device, search controls based on the firsttiming output, information associated with an operating mode of thenetwork device, and prior timing information; and generating, at thenetwork device, a second timing output in response to the searchcontrols and based on the correlation moduli, the second timing outputrepresenting a more accurate approximation of a burst start time thanthe first timing output.
 31. The method of claim 30, where thegenerating the search controls includes: selecting one of the priortiming information or the first timing output.
 32. The method of claim30, where the search controls include start and size information. 33.The method of claim 30, where the generating correlation moduli occursmultiple times in a clock cycle.
 34. The method of claim 30, where thegenerating correlation moduli includes: performing steeply slopedautocorrelation on the received signal.
 35. The method of claim 34,where the correlation moduli includes a steeply sloped peak in responseto a presence of a predetermined sequence in the received signal. 36.The method of claim 34, where the correlation moduli includes a steeplysloped peak in response to a presence of a predetermined sequence in apreamble of the received signal.
 37. The method of claim 34, where theinformation associated with an operating mode of the network deviceincludes information identifying one of a traffic mode, in which thenetwork device receives data, or a ranging mode, in which the networkdevice performs a ranging operation.
 38. A device comprising: means forreceiving a signal; means for generating correlation moduli based on thereceived signal; means for generating a first timing output based on thegenerated correlation moduli; means for generating one or more controlsbased on the first timing output and information associated with anoperating mode of the device; and means for generating, in response tothe one or more controls, a second timing output based on thecorrelation moduli, the second timing output representing a moreaccurate approximation of a burst start time than the first timingoutput.
 39. The device of claim 38, where the means for generating theone or more controls includes: means for selecting one of prior timinginformation or the first timing output.
 40. The device of claim 38,where the one or more controls include start and size information. 41.The device of claim 38, where the means for generating the correlationmoduli generates the correlation moduli multiple times in a clock cycle.42. The device of claim 38, where the means for generating thecorrelation moduli includes: means for performing a steeply slopedautocorrelation on the received signal.
 43. The device of claim 42,where the correlation moduli includes a steeply sloped peak in responseto a presence of a predetermined sequence in the received signal. 44.The device of claim 42, where the correlation moduli includes a steeplysloped peak in response to a presence of a predetermined sequence in apreamble of the received signal.
 45. The device of claim 38, where theinformation associated with an operating mode of the device includesinformation identifying one of a traffic mode, in which the devicereceives data, or a ranging mode, in which the device performs a rangingoperation.
 46. The device of claim 38, where the device corresponds to acable modem termination system (CMTS) of a cable network.
 47. A methodcomprising: receiving, at a network device, a signal; generating, at thenetwork device and based on the signal, correlation moduli; generating,at the network device, a first burst start time based on the correlationmoduli; and identifying, at the network device, a maximum correlationmodulus of the correlation moduli; and generating, at the networkdevice, a second burst start time based on the maximum correlationmodulus, the second burst start time being more accurate than the firstburst start time.
 48. The method of claim 47, where the identifying themaximum correlation modulus includes: identifying the maximumcorrelation modulus based on an operating mode of the network device,the operating mode including one of a traffic mode, in which the networkdevice receives data, or a ranging mode, in which the network deviceperforms a ranging operation.
 49. The method of claim 47, where thecorrelation moduli includes a steeply sloped peak in response to apresence of a predetermined sequence in a preamble of the receivedsignal.